MRP_py

MRP_py parametrizes covalently modified amino acid residues for molecular dynamics simulations, generating atomistic force-field parameters and RESP-derived charges for post-translationally modified (PTM) residues.


Key Features:

  • Integration with AmberTools and Gaussian: Integrates with AmberTools (requires version 15 or higher) and Gaussian to enable molecular modeling and quantum mechanical calculations.
  • Charge Derivation via RESP: Derives partial charges using the Restrained Electrostatic Potential (RESP) fitting procedure.
  • Force Constant Optimization: Obtains and adapts force constants by rewriting parameters from protein-specific or GAFF (General AMBER Force Field) databases.
  • Interface Parameterization: Systematically parameterizes the interface between modified residues and surrounding protein residues.
  • Database Compatibility: Supports parameter extraction and compatibility with a variety of protein-specific databases.

Scientific Applications:

  • Molecular dynamics of modified proteins: Enables MD simulations of proteins containing covalently modified amino acid residues.
  • Post-translational modification modeling: Facilitates parameterization of post-translational modifications (PTMs).
  • Covalent inhibitor modeling and interface analysis: Supports parameterization for covalent binding of small-molecule inhibitors and analysis of interfacial interactions between modified residues and host proteins.

Methodology:

RESP charge derivation; adaptation and rewriting of force constants from protein-specific or GAFF databases; quantum mechanical calculations via Gaussian; integration with AmberTools (requires v15+).

Topics

Details

License:
GPL-3.0
Tool Type:
command-line tool
Programming Languages:
Python
Added:
1/18/2021
Last Updated:
3/1/2021

Operations

Publications

Sahrmann PG, Donnan PH, Merz KM, Mansoorabadi SO, Goodwin DC. MRP.py: A Parametrizer of Post-Translationally Modified Residues. Journal of Chemical Information and Modeling. 2020;60(10):4424-4428. doi:10.1021/acs.jcim.0c00472. PMID:32672967.

PMID: 32672967
Funding: - Division of Chemistry: CHE-1555138 - Division of Molecular and Cellular Biosciences: MCB-1616059